How I Built a DNA Mutation Predictor Using ESM-2 and XGBoost (Open Source) As a Highskewler :]

KleosOmen — Fri, 04 Sep 2026 05:34:23 +0000

I built a tool that tells you if a DNA mutation causes disease. No cloud API. No paid service. Just a Python CLI on your laptop.

Here's how it works — and how you can run it yourself.

The Problem
hen a single nucleotide changes in DNA (a missense mutation), it can alter a protein's function. Some changes cause disease. Most don't. ClinVar — the NIH's database of known variants — has ~2,800 classified missense mutations. I wanted to build a classifier that could predict pathogenicity from sequence alone.

The Stack

ESM-2 (facebook/esm2_t30_150M_UR50D) — a 150M-parameter protein language model from Meta. It reads protein sequences and produces 640-dimensional embeddings that capture evolutionary and structural information.
XGBoost — gradient boosted trees, trained on 40 selected features from the ESM-2 embed-dings.
scikit-learn — feature selection (SelectKBest) and scaling (StandardScaler).

No deep learning at inference time. The ESM-2 embeddings are computed once and fed into a lightweight XGBoost model. The result: 82.5% accuracy on a 2,792-sample ClinVar dataset.

How It Works

You input a protein symbol + mutation (e.g., BRCA1 A1708E)
The tool fetches the protein sequence from UniProt
ESM-2 produces a 640-dim embedding for the mutated sequence
XGBoost classifies: PATHOGENIC or BENIGN
You get a confidence score + a protein feature graph

Running It

git clone https://github.com/NOOBHEKER/dna-mutation-predictor.git
cd dna-mutation-predictor
pip install -r requirements.txt
python -m src.cli

Or double-click predict.bat on Windows — it sets up everything automatically.

What I Learned

ESM-2 embeddings contain enough signal to classify pathogenicity without hand-crafted features
Feature selection matters: 40 out of 640 dimensions outperformed the full embedding
CPU inference is slow (~30s per prediction) but acceptable for research use
The hardest part was cleaning ClinVar data, not training the model

Try It
The project is open source under MIT license. Clone it, break it, improve it.

GitHub: https://github.com/NOOBHEKER/dna-mutation-predictor
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If it's useful to your research, I'd appreciate a star or a coffee.

DEV Community: KleosOmen

How I Built a DNA Mutation Predictor Using ESM-2 and XGBoost (Open Source) As a Highskewler :]